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[WIP] Introduce additional_labels #306

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AntonioMirarchi
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@AntonioMirarchi AntonioMirarchi commented Mar 15, 2024

This PR proposes several enhancements to enable the usage of extra arguments in both training and inference. The key modifications include

  • standardizing the naming conventions for all extra fields across different data loaders;
  • removing q and s as explicit args in the forward;
  • introducing additional labels through a new dictionary for model initialization, example:
additional_labels:
     tensornet_q:
        label: total_charge
        learnable: true
        init_value: 0.1
  • add TensornetQ nn.Module
  • extra args expansion from molecule-wise to atom-wise inside the model
  • tensornet_q tested with total_charge and partial_charges, reproducibility achieved
  • rewriting some tests according to the new methods
  • allowing multiple additional_methods implementation
    At the moment only 'tensornet_q' supported as additional_methods but more can be added

@AntonioMirarchi AntonioMirarchi mentioned this pull request Jan 27, 2025
@AntonioMirarchi
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Closing this PR for now as an alternative, more streamlined solution has been proposed in #353.

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3 participants